Assessing predictors of elevated distress among newly-arrived humanitarian immigrants in Maryland

AAFREEN MAHMOOD, MSPH

Forced Displacement and Mental Health

65.6 million displaced worldwide

Unaddressed mental health (MH) needs upon arrival to U.S.

Common diagnoses: PTSD, depression, anxiety

Poor MH poor social functioning, productivity

U.S. emphasis on economic self-sufficiency

Good MH critical to resettlement success

Source: Migration Policy Institute

Triple Trauma Paradigm

Pre-migration Migration Post-migration

Increased risk of

developing

mental disorders

Elevated distress

Women are especially vulnerable to stressors in migration journey

• Pre- and during migration: Sexual and gender-based, intimate partner violence

• Post-migration: disrupted gender roles, loss of social support, acculturation

Study Aim

Humanitarian immigrant type: proxy for migration experiences & stressors

Hypothesis: SIVs have lower odds & asylees have higher odds of demonstrating elevated distress in MH screenings; gender moderates this relationship.

Refugee Asylee SIV holder

Aim: Assess predictors of elevated distress (positive RHS-15 screening) among

newly-arrived humanitarian immigrants in Maryland, particular focus on women

Data Source: Refugee Health Screener-15

Validated among refugee populations

Used in Maryland health assessments

Q1-13: symptoms predictive of PTSD, depression, and anxiety

Q14: coping ability

Q15: distress thermometer

Positive screen:

◦ Symptom total (Q1-14) > 12

◦ Distress thermometer (Q15) > 5

Not a diagnostic tool

Source: Pathways to Wellness

Methods ◦ Maryland Immigrant and Refugee Information System (MIRIS) database

◦ Secondary analysis of RHS-15 screening data (2014-2017)

◦ Inclusion criteria

◦ Refugees, Asylees, and SIV holders (aged 18 and above)

◦ Exclusion criteria

◦ ”Delayed Asylees”

◦ Incomplete/non-existent mental health screening

◦ Bivariate & multivariate logistic regression

◦ Dependent variable: screening positive or negative on RHS-15

◦ Independent variables: age, gender, immigrant type, interpreter type

◦ Assess gender as moderating factor

Total Sample

(n=4,385)

Refugees

(n=2.767)

Asylees

(n=789)

SIV holders

(n=829)

Age Category (%)

18-24 24.0 23.6 26.4 23.3

25-55 70.5 69.1 69.7 76.0

56 and up 5.5 7.4 3.9 0.7

Sex (%)

Male 53.4 54.8 48.3 53.5

Female 46.6 45.2 51.7 46.5

Country of Origin (%)

Afghanistan 21.1 4.7 0.5 95.4

Burma-Myanmar 15.3 24.0 0.5 0

DRC 7.6 11.2 2.5 0

Ethiopia 10.3 7.4 31.1 0

Iraq 8.1 11.4 0.8 4.0

Syria 6.0 9.4 0.1 0.4

Results

Results

Top countries of origin for total sample:

◦ Afghanistan, Burma-Myanmar, DRC, Ethiopia, Iraq, Syria

◦ Heterogeneity in country of origin for refugees & asylees, not SIV holders

27% of total sample screened positive

Higher proportion screening positive:

◦ Females

◦ Individuals aged 56+

◦ Individuals from Afghanistan, Iraq, & Syria

0

5

10

15

20

25

30

35

Refugees Asylees SIV holders

Pe

rce

nta

ge

Proportion Screening Positive on RHS-15

Pearson’s chi-squared test: p<0.001

Results: Regression of Positive RHS-15 Screening on Independent Variables

Bivariate Multivariate

Odds Ratio 95% CI p-value Odds Ratio 95% CI p-value

Immigrant Type

(reference: refugee)

Asylee 0.65 (0.53 – 0.79) 0.000 0.73 (0.54 – 0.99) 0.041

SIV holder 1.26 (1.07 – 1.49) 0.007 0.89 (0.68 – 1.16) 0.388

Age (measured continuously)

Under 60 years 1.02 (1.01 – 1.02) 0.000 1.03 (1.02 – 1.03) 0.000

Over 60 years 1.00 (0.97 – 1.04) 0.920 0.94 (0.90 – 0.98) 0.004

Sex (reference: male) 1.46 (1.27 – 1.66) 0.000 1.32 (1.12 – 1.57) 0.001

Interpreter Type

(reference: no interpreter used)

Telephonic Service 2.02 (1.64 – 2.49) 0.000 1.52 (1.21 – 1.91) 0.000

Bilingual Staff 0.97 (0.79 – 1.20) 0.005 0.80 (0.63 – 1.02) 0.068

Contracted 1.59 (1.28 – 2.00) 0.000 1.28 (1.01 – 1.62) 0.045

Other 2.49 (1.80 – 3.44) 0.000 2.00 (1.41 – 2.82) 0.000

Interaction Terms

Female x Asylee - - - 0.87 (0.59 – 1.30) 0.503

Female x SIV - - - 1.74 (1.22 – 2.48) 0.002

Discussion

Asylees had lower odds of screening positive on RHS-15

◦ Variation in time spent in U.S. before screened

◦ Existence of social networks upon arrival

◦ Social support systems identified as buffer for distress

Higher odds of screening positive among females

◦ Gendered stressors and more comfort with communicating distress

Discussion SIV holders’ odds ratio non-significant, but strong interaction term for SIV women

Gender-specific stressors:

◦ Younger, less educated, less English proficient

◦ Strong joint family structures in Afghanistan

◦ Afghan tradition of family support during childbirth, child rearing

◦ Loss of social support isolation, depression, somatic complaints

◦ Disruption of traditional gender roles

SIV-specific stressors

◦ Bypass cultural orientations, may come to U.S. less prepared with higher expectations

◦ More benefits in home countries than in U.S.

◦ Difficulty in finding employment frustration and disappointment

Study Limitations Limitation Impact

Nearly all SIV holders from Afghanistan Limits extent to which results can be

attributed to immigrant type vs. country

No information on asylee type (affirmative vs. derivative)

Better understand impact of different

migration experiences

No information on asylum-seekers Cannot study impact of insecure status

distress

No information on other characteristics (e.g. education or income level, English proficiency,

marital status, family members)

Cannot control for other important

contributors/buffers to distress

Conclusions & Implications Humanitarian immigrants arriving in Maryland with elevated distress

◦ Afghan SIV women may most likely be in need of MH service referrals

Findings inform MDH service planning & resettlement agencies activities

◦ Maryland in top 10 states of SIV holder arrivals

◦ Travel bans, stakeholders rely on SIV admissions to stay operational

◦ Focus on reducing post-migration stressors

Acknowledgements Maryland Department of Health, Office of Immigrant Health

◦ Dipti Shah, MPH

◦ Lisa Paulos, MPH, RN

Johns Hopkins Bloomberg School of Public Health

◦ Judith Bass, PhD

◦ Mary Elizabeth Hughes, PhD

◦ Georgia Michlig, MA

◦ Center for Humanitarian Health

◦ Johns Hopkins Global Mental Health Group

Questions? Contact me at amahmo10@jhmi.edu